Digital image processing apparatus and method

ABSTRACT

A digital image processing apparatus and method are provided. The digital image processing apparatus includes: a Y component processing unit receiving a Y component and performing edge enhancement processing and first noise reduction processing on the Y component by using a memory allocated to the Y component; and a CbCr processing unit receiving a Cb component and a Cr component, and performing false color suppression processing and second noise reduction processing on the Cb component and the Cr component by using a memory allocated to the Cb component and the Cr component, where the Y component, the Cb component and the Cr component are variables of the YCbCr color space.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority under 35 U.S.C. 119(a) to KoreanPatent Application No. 10-2011-0133743 filed on Dec. 13, 2011, in theKorean Intellectual Property Office, which is incorporated by referenceherein in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Embodiments of the inventive concept relate to a digital imageprocessing apparatus and method configured in consideration of effectivememory use.

2. Description of the Related Art

Operations for improving digital image quality include edge enhancement,noise reduction, false color suppression, and the like.

Edge enhancement involves determining whether an edge of an image ispresent in the image, and then adjusting pixel values in the edge regionto enhance image sharpness (clarity or definition). Noise reductionrefers to performing low pass filtering to reduce noise. The low passfiltering may be performed by using an averaging filter or a medianfilter. False color suppression involves eliminating false colors froman image. False color is generated in performing color interpolation inan image signal processing system, and the false color suppressionoperation is performed by determining whether a false color is presentand then eliminating a false color.

In order to perform edge enhancement, noise reduction, false colorsuppression, and the like, a memory is required. In general, a staticrandom access memory (SRAM) is used as a memory for performing theseoperations. Accordingly, an increase in the size of the memory in useleads to an increase in the size of an image sensor chip.

SUMMARY OF THE INVENTION

An aspect of the inventive concept provides a digital image processingapparatus capable of effectively using a memory.

Another aspect of the inventive concept provides a digital imageprocessing method for achieving the object of the inventive concept.

According to an aspect of the inventive concept, there is provided adigital image processing apparatus including: a Y component processingunit receiving a Y component and performing edge enhancement processingand first noise reduction processing on the Y component by using amemory allocated to the Y component; and a CbCr processing unitreceiving a Cb component and a Cr component, and performing false colorsuppression processing and second noise reduction processing on the Cbcomponent and the Cr component by using a memory allocated to the Cbcomponent and the Cr component, where the Y component, the Cb componentand the Cr component are variables of a YCbCr color space.

According to another aspect of the inventive concept, there is provideda digital image processing method including: allocating memories to a Ycomponent, a Cb component, and a Cr component; performing edgeenhancement processing and first noise reduction processing on the Ycomponent by using a memory allocated to the Y component; and performingfalse color suppression processing and second noise reduction processingon the Cb component and the Cr component by using a memory allocated tothe Cb component and the Cr component.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features and other advantages of theinventive concept will be more clearly understood from the followingdetailed description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 is a schematic block diagram showing a configuration of a digitalimage processing apparatus according to an embodiment of the inventiveconcept;

FIG. 2 is a flow chart illustrating a digital image processing methodaccording to an embodiment of the inventive concept;

FIG. 3 is a flow chart illustrating an operation of processing a Ycomponent in image data;

FIG. 4 is a graph for explaining a step of setting a region gain in themethod for processing the Y component shown in FIG. 3;

FIG. 5 is a graph for explaining a step of calculating an adjustmentgain by adjusting a region gain in the method for processing the Ycomponent shown in FIG. 3;

FIG. 6 is a flow chart illustrating a step of processing a Cb componentand a Cr component of image data in the method for processing a digitalimage according to an embodiment of the inventive concept shown in FIG.2; and

FIG. 7 is a flow chart illustrating a step of performing a false colorsuppressing operation in the method for processing the Cb component andthe Cr component shown in FIG. 6.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Embodiments of the inventive concept will be described in detail withreference to the accompanying drawings. The invention may, however, beembodied in many different forms and should not be construed as beinglimited to the embodiments set forth herein. Rather, these embodimentsare provided so that this disclosure will be thorough, and will fullyconvey a scope of the invention to those skilled in the art. In thedrawings, the shapes and dimensions of elements may be exaggerated forclarity, and the same reference numerals will be used throughout todesignate the same or like components.

FIG. 1 is a schematic block diagram showing a configuration of a digitalimage processing apparatus according to an embodiment of the inventiveconcept. The digital image processing apparatus according to anembodiment of the inventive concept may include a first memory unit 10,an edge region discrimination unit 20, a demultiplexer 25, an edgeenhancement unit 30, a Y noise canceling unit 40, a first multiplexer50, a second memory unit 60, a low pass filter 70, a false colorsuppression unit 80, and a second multiplexer 90. The first memory unit10 may include a first line memory 11 and a first memory controller 12.The second memory unit 60 may include a second line memory 61 and asecond memory controller 62.

The blocks illustrated in FIG. 1 have the following functions.

The first memory unit 10, including the first line memory 11 and thefirst memory controller 12, receives an input Y component Y_in andgenerates Y matrix data Y_mt.

The first memory controller 12 outputs a first control signal con1 towrite first write data dint in the first memory and read first read datadout1 from the first line memory 11. The first memory unit 10 may alsogenerate the Y matrix data Y_mt by using the input Y component Y_in andthe first read data dout1 which has been read from the first memory 11.The Y matrix data Y_mt may be 5×5 matrix.

In response to the first control signal con1, the first line memory 11stores the first write data din1 and outputs the first read data dout1.The first line memory 11 may have a static random access memory (SRAM)type line memory having an address space corresponding to an input imagewidth. In this case, the first line memory 11 may have four SRAM typeline memories, and each of the SRAM type line memories may be an 8-bitmemory. The frequency of a clock signal input to the first line memory11 may be ½ of the frequency of an operation clock of the digital imageprocessing apparatus.

The edge region discrimination unit 20 receives the Y matrix data Y_mt,detects edges, discriminates edge regions by using the detected edges,and outputs Y data (Y_h, Y_m, Y_l) relating to each edge region. Forexample, the edge region discrimination unit 20 may generate a localmatrix within the Y matrix data Y_m, detect edges in consideration offour directions, such as a vertical direction, a horizontal direction, adiagonal direction (the diagonal direction may extend from a pixelresiding in the first row and first column of a matrix, toward a pixelresiding in the last row and last column of the matrix), and a reversediagonal direction (the reverse diagonal direction may extend from apixel residing in the first row and last column of the matrix, toward apixel residing in the last row and first column of the matrix), and theedge region discrimination unit 20 may discriminate the edge regionsinto a low edge region, a middle edge region, and a high edge region.The edge region discrimination unit 20 outputs high edge Y data Y_h,middle edge Y data Y_m, and low edge Y data Y_l according to thediscriminated regions. Details of a method of discriminating the edgeregion will be described with reference to FIG. 3.

In response to a filtering enable signal Ylpf_en, the demultiplexer 25outputs the low edge Y data Y_l to the edge enhancement unit 30 or the Ynoise reducer.

The edge enhancement unit 30 receives the high edge Y data Y_h and themiddle edge Y data Y_m, or the high edge Y data Y_h, the middle edge Ydata Y_m, and the low edge Y data Y_i and outputs an edge-enhanced Ycomponent YEE. In this case, the edge enhancement unit 30 maysequentially calculate a region gain and an adjustment gain with respectto the input Y component (i.e., high edge Y data Y_h, the middle edge Ydata Y_m, and/or the low edge Y data Y_l), calculate a brightnessdifference, and the edge-enhanced Y component YEE by using theadjustment gain, the brightness difference, and the input Y component. Aspecific operation of generating the edge-enhanced Y component YEE willbe described later with reference to FIGS. 3 through 5.

The Y noise reducer 40 receives the low edge Y data Y_l and outputs anoise-reduced Y component YNR. A specific operation of the Y noisereducer 40 will be described later with reference to FIG. 3.

In response to the filtering enable signal Ylpf_en, the firstmultiplexer 50 outputs the edge-enhanced Y component YEE or thenoise-reduced Y component YNR as a final Y component YO. Namely, the lowedge Y data Y_l (i.e., the Y component of the low edge region) isedge-enhanced through the edge enhancement unit 30 so as to be output asthe final Y component YO or may be noise-reduced through the Y noisereducer 40 so as to be output as the final Y component YO.

The second memory unit 60, including a second line memory 61 and asecond memory controller 62, receives an input Cb component Cb_in and aninput Cr component Cr_in and generates Cb matrix data Cb_mt and Crmatrix data Cr_mt. The Y component, Cb, and Cr may be variables of theYCbCr color space where the Y component may be brightness (luma), Cb andCr may be blue-difference and red-difference chroma components.

The second memory controller 62 outputs a second control signal con2 towrite second write data dint in the second line memory 61 and readsecond read data dout2 from the second line memory 61. The second memorycontroller 62 may also generate the Cb matrix data Cb_mt and the Crmatrix data Cr_mt by using the input Cb component Cb_in and the input Crcomponent Cr_in and the second read data dout2 read from the second linememory 61. In detail, the second memory controller 62 may generate theCb matrix data Cb_mt and the Cr matrix data Cr_mt by using the Cb dataand the Cr data obtained by averaging-filtering the input Cb componentCb_in and the input Cr component Cr_in and the second read data dout2.The second memory controller 62 may average-filter the input Cbcomponent Cb_in and the input Cr_component Cr_in, respectively, toperform YCrCb 4:2:2 compression. Each of the Cb matrix data Cb_mt andthe Cr matrix data Cr_mt may be 5×5 matrix data.

In response to the second control signal con2, the second line memory 61stores the second write data dint and outputs the second read datadout2. The second line memory 61 may include an SRAM type line memoryhaving an address space corresponding to an input image width. In thiscase, the second line memory 61 may have four SRAM type line memories,and each of the four SRAM type line memories may be an 8-bit memory. Thefrequency of a clock signal input to the second line memory 61 may be ½of the frequency of an operation clock of the digital image processingapparatus.

The low pass filter 70 low-pass-filters the Cb matrix data Cb_mt and theCr matrix data Cr_mt to generate filtered Cb data Cb_lpf and filtered Crdata Cr_lpf.

The false color suppression unit 80 receives the filtered Cb data Cb_lpfand filtered Cr data Cr_lpf and the Y component Y_cr of the currentpixel and performs a false color suppression operation. When the falsecolor suppression operation is performed on the pixel at a position(x,y), the Y component of the current pixel may have a size of the Ycomponent of the pixel at (x,y) position. Also, as mentioned above, whenthe Y matrix data Y_mt is 5×5 matrix data Y11 to Y55, the Y componentY_cr of the current pixel may be Y33 of the Y matrix data Y_mt. Adetailed operation of the false color suppression unit 80 will bedescribed with reference to FIG. 7.

In response to a false enable signal Cfcs_en, the second multiplexer 90outputs one of the filtered Cb data Cb_lpf and filtered Cr data Cr_lpfand an output signal from the false color suppression unit 80 as finalCb data CbO and final Cr data CrO. In some embodiments, the first memoryunit 10, the edge region discrimination unit 20, the edge enhancementunit 30, the Y noise canceling unit 40, the demultiplexer 25 and thefirst multiplexer 50 may cooperatively operate as a Y componentprocessing unit. Also, the second memory unit 60, the low pass filter70, the false color suppression unit 80 and the second multiplexer 90may operate cooperatively as a CbCr processing unit.

FIG. 2 is a flow chart illustrating a digital image processing methodaccording to an embodiment of the inventive concept.

The digital image processing method according to an embodiment of theinventive concept will be described with reference to FIG. 2 as follows.

First, a memory is allocated to each of the Y component, the Cbcomponent and the Cr component (S100). The image sensor according to anembodiment of the inventive concept may include a memory in order toprocess image data. The memory may be a SRAM type line memory and aplurality of memories may be provided. When the provided memories are aplurality of line memories, 2N memories are allocated to the Ycomponent, and 2N line memories may be allocated to the Cb component andthe Cr component. Here, N may be a natural number. Also, in this case, Nnumber of line memories may be allocated to each of the Cb component andthe Cr component. For example, four line memories may be allocated tothe Y component and four line memories may be allocated to the Cbcomponent and the Cr component.

Next, edge enhancement processing and noise reduction processing areperformed on the Y component (S200). Also, false color suppressionprocessing and noise reduction processing are performed on the Cb and Crcomponents (S300). Steps S200 and S300 may be performed concurrently.

FIG. 3 is a flow chart illustrating the step (S200) of processing a Ycomponent in image data in the digital image processing methodillustrated in FIG. 2.

The step S200 of processing the Y component will be described withreference to FIG. 3 as follows.

An edge of the Y component (S210) is detected. When an edge of the Ycomponent is detected, with respect to the Y component, the edge may bedetected in consideration of four directions such as a verticaldirection, a horizontal direction, a diagonal direction, and a reversediagonal direction by using a 5×5 window operation. For example, the Ycomponent may be 5×5 Y matrix data Y_mt. In this case, a 3×3 localmatrix may be generated in the 5×5 Y matrix data Y_mt, and then, an edgemay be detected in consideration of four directions such as the verticaldirection, the horizontal direction, the diagonal direction, and thereverse diagonal direction.

Next, a gain is set for the Y component (S222 to S226).

First, an edge region is determined by using the edge detected in stepS210 (S222). In this case, an edge map may be calculated by performing5×5 mask generation processing on the Y component and simultaneouslyperforming 3×3 local mask processing in a 5×5 global mask. Through theedge map, the edge region of the Y component may be determined as a lowedge region, a middle edge region, and a high edge region. For example,when the size of the edge map EM(x,y) with respect to a pixel at theposition (x,y) is smaller than a first edge value, the correspondingpixel may be determined to be included in (or belong to) the low edgeregion. When the size of the edge map EM(x,y) is greater than or equalto the first edge value but smaller than a second edge value, thecorresponding pixel may be determined to be included in the middle edgeregion. When the size of the edge map EM(x,y) is greater than or equalto the second edge value, the corresponding pixel may be determined tobe included in the high edge region. The second edge value may begreater than the first edge value.

A region gain according to the edge region is set (S224).

FIG. 4 is a graph for explaining the step (S224) of setting a regiongain in the step (S200) of processing the Y component shown in FIG. 3.The method of setting a region gain will be described with reference toFIG. 4 as follows.

A region gain with respect to a low edge may be set to be a low gain,and a region gain with respect to a high edge region may be set to be ahigh gain, and a region gain with respect to a middle edge region may beset to be a gain value determined in proportion to the value of the edgemap among gain values between the low gain and the high gain. Forexample, when the pixel at the position (x,y) is included in the lowedge region according to the results of performing step S222, the regiongain with respect to the pixel may be set to be a low gain. If the pixelat the position (x,y) is included in the middle edge region according tothe results of performing step S222, the region gain with respect to thepixel may be set to be a gain value determined in proportion to the sizeof the edge map EM(x,y) of the pixel among values between the low gainand the high gain. If the pixel at the position (x,y) is included in thehigh edge region according to the results of performing step S222, thegain region with respect to the pixel may be set to be a high gain. Thehigh gain may have a gain value greater than that of the low gain.

Next, an adjustment gain is calculated by adjusting the region gainaccording to illumination (i.e., intensity of illumination, luminousintensity, or illuminance) (S226).

FIG. 5 is a graph for explaining the step S226 of calculating anadjustment gain by adjusting a region gain and in the step of processingthe Y component shown in FIG. 3. The method of calculating an adjustmentgain will be described with reference to FIG. 5 as follows.

With respect to a normal region in which the size of the Y component isgreater than or equal to a first illumination value and smaller than asecond illumination value, an adjustment gain may have a value equal tothat of the region gain set in step S224. With respect to a dark regionin which the size of the Y component is smaller than the firstillumination value, the adjustment gain may have a gain value determinedin proportion to the size of the Y component among gain values betweenthe low gain and the region gain set in step S224. With respect to abright region in which the size of the Y component is greater than orequal to the second illumination value, the adjustment gain may have again value determined in inverse proportion to the size of the Ycomponent among gain values between the region gain set in step S224 andthe low gain. For example, when the size Y(x,y) of the Y component ofthe pixel at the position (x,y) is greater than or equal to the firstillumination value and smaller than the second illumination value, thepixel may be determined to be included in the normal region, and theadjustment gain with respect to the pixel may have the same value asthat of the region gain with respect to the pixel set in step S224. Ifthe size Y(x,y) of the Y component of the pixel at the position (x,y) issmaller than the first illumination value, the pixel may be determinedto be included in the dark region, and the adjustment gain with respectto the pixel may have a gain value determined in proportion to the sizeY(x,y) of the Y component of the pixel among gain values between the lowgain and the region gain with respect to the pixel set in step S224.

If the size Y(x,y) of the Y component of the pixel at the position (x,y)is greater than or equal to the second illumination value, the pixel maybe determined to be included in the bright region, and the adjustmentgain with respect to the pixel may have a gain value determined ininverse proportion to the size Y(x,y) of the Y component of the pixelamong the gain values between the region gain with respect to the pixelset in step S224 and the low gain.

Also, a brightness difference is calculated by using the Y component(S230). In this case, averaging-filtering may be performed on the centerweight with respect to the Y component to calculate a blurred Ycomponent, and then, the blurred Y component may be subtracted from theY component, thus calculating a brightness difference. For example, whenthe size of the Y component with respect to the position (x,y) isY(x,y), the size of the blurred Y component is Yblur(x,y), and thebrightness difference of the pixel is Ydiff(x,y). The brightnessdifference may be determined by Equation shown below:

Ydiff(x,y)=Y(x,y)−Yblur(x,y)

Here, the brightness difference of the pixel has a value correspondingto brightness of the pixel and the brightness of pixels neighboring thepixel.

Step S230 may be performed simultaneously with the steps S222 to S226 ofcalculating the foregoing gain, or before or after.

Next, in step S240, the edge-enhanced Y component is calculatedaccording to the adjustment gain calculated in step S226 and thebrightness difference calculated in step S230 (S240). In this case, avalue obtained by adding the value obtained by multiplying theadjustment gain and the brightness difference to the Y component may becalculated as the edge-enhanced Y component. The edge-enhanced Ycomponent may be obtained by multiplying the adjustment gain and thebrightness difference and adding the result to the Y component. Forexample, when the adjustment gain at the position (x,y) is EG(x,y), thebrightness difference with respect to the pixel is Ydiff(x,y), the Ycomponent of the pixel is Y(x,y), and the edge-enhanced Y component withrespect to the pixel is YEE(x,y), then, the edge-enhanced Y componentYEE(x,y) may be calculated by the Equation shown below:

YEE(x,y)=EG(x,y)×Ydiff(x,y)+Y(x,y)

Also, noise reduction processing is performed on the Y component of thelow edge region (S250). Averaging filtering using a variable centerweight is performed on the Y component at the low edge region, therebyperforming low pass filtering on the Y component of the low edge regionto calculate a noise-reduced Y component (YNR) (namely, a filtered Ycomponent). As a result, noise reducing based on a 5×5 window availablefor center weight controlling is performed on the Y component of the lowedge region.

Next, a final Y component is calculated (S260). In this case, the finalY component of the middle edge region and the high edge region may be anedge-enhanced Y component, and the final Y component of the low edgeregion may be a noise-reduced Y component YNR (i.e., a filtered Ycomponent). For example, it is assumed that a final Y component withrespect to the pixel at the position (x,y) is YO(x,y). If the pixel isincluded in the middle edge region or the high edge region, the final Ycomponent YO(x,y) may be the edge-enhanced Y component YEE(x,y) withrespect to the pixel calculated in step S240. If the pixel is includedin the low edge region, the final Y component YO(x,y) may be thefiltered Y component with respect to the pixel calculated in step S250.

Next, when the final Y component has an overflow or an underflow, thefinal Y component is clipped and output (S270).

FIG. 6 is a flow chart illustrating a step (S300) of processing the Cbcomponent and the Cr component of image data in the digital imageprocessing method according to an embodiment of the inventive conceptshown in FIG. 2.

The method for processing the Cb component and the Cr component will nowbe described with reference to FIG. 6.

First, noise reducing is performed on the Cb component and the Crcomponent, respectively (S310). Averaging filtering using the variablecenter weight may be performed on each of the Cb component and the Crcomponent, thereby performing low pass filtering on the Cb component andthe Cr component to calculate the filtered Cb component and the filteredCr component. As a result, noise reducing based on a 5×5 windowavailable for center weight controlling is performed on each of the Cbcomponent and the Cr component. This may be performed together with a5×5 mask generation with respect to the Cb component and the Crcomponent.

Thereafter, it is determined whether a false color suppression operationhas been enabled (S320).

When the false color suppression operation has not been enabledaccording to the determination result in step S320, the filtered Cbcomponent and the filtered Cr component calculated in step S310 aregenerated as a final Cb component and a final Cr component, respectively(S330).

If the false color suppression operation has been enabled according tothe determination result in step S320, the false color suppressionoperation is performed on the filtered Cb component and the filtered Crcomponent to generate a final Cb component and a final Cr component(S340).

And then, when the final Cb component and the final Cr componentgenerated in step S330 or the final Cb component and the final Crcomponent generated in step S340 have an overflow or an underflow, thefinal Cb component and/or the final Cr component are clipped, and theresultant components are output (S350).

FIG. 7 is a flow chart illustrating a step (S340) of performing a falsecolor suppressing operation in the method for processing the Cbcomponent and the Cr component shown in FIG. 6.

The false color suppression processing (S340) will be described withreference to FIG. 7 as follows.

Hereafter, it is assumed that the false color suppression processing isperformed on the pixel at the position (x,y).

First, it is determined whether the pixel is included in the brightregion (S341). For example, when the size of the Y component Y(x,y) ofthe pixel is greater than or equal to the second illumination value, thepixel may be determined to be in the bright region.

When the pixel is determined to be in the bright region according to thedetermination result in step S341, it is determined whether the pixelhas a gray tone based on the filtered Cb component and the filtered Crcomponent of the pixel calculated in step S310 (S342).

When it is determined that the pixel is not in the bright regionaccording to the determination result in step S341 or when it isdetermined that the pixel does not have a gray tone according to thedetermination result in step S342, it is determined whether the pixel isincluded in the dark region (S343). For example, when the size of the Ycomponent Y(x,y) of the pixel is smaller than the first illuminationvalue, the pixel may be determined to be in the dark region.

When it is determined that the pixel is included in the dark regionaccording to the determination result in step S343, it is determinedwhether the pixel has a gray tone based on the filtered Cb component andthe filtered Cr component of the pixel calculated in step S310 (S344).

When it is determined that the pixel has a gray tone according to theresult of step S342 and the result of step S344, the false colorsuppression operation is performed and the false color-suppressed Cb andCr components are generated as final Cb and Cr components, respectively(S345).

Namely, in an embodiment of the inventive concept, whether there is afalse color may be determined based on a false color detection thresholdvalue, and then, a false color may be eliminated. For example, whetherboth the Cb component and the Cr component have a gray tone isdetermined by using the false color detection threshold value. When boththe Cb component and the Cr component have a gray tone, the false colormay be eliminated such that the Cb component and the Cr component of thecorresponding pixel may have more gray tone.

When it is determined that the pixel is not included in the dark regionaccording to the determination result in step S343 or when the pixeldoes not have a gray tone according to the determination result in stepS344, the filtered Cb component and the filtered Cr component calculatedin step S310 are generated as a final Cb component and a final Crcomponent (S346).

As a result, when a particular pixel is in the bright region or darkregion and has a gray tone, false color suppression processing isperformed on the particular pixel.

The digital image processing method as described above may be used in adigital camera, a mobile phone, a PC camera, a personal digitalassistant (PDA), and the like.

As set forth above, according to embodiments of the invention, thedigital image processing apparatus and method can efficiently use thememory (or memories), the size of the memory required for performing theimage processing operation can be reduced, and as a result, the size ofan image sensor chip can also be reduced.

While the inventive concept has been shown and described in connectionwith the described embodiments, it will be apparent to those skilled inthe art that modifications and variations can be made without departingfrom the spirit and scope of the invention as defined by the appendedclaims.

What is claimed is:
 1. A digital image processing apparatus comprising: a y component processing unit receiving a Y component and performing edge enhancement processing and first noise reduction processing on the Y component by using a memory allocated to the Y component; and a CbCr processing unit receiving a Cb component and a Cr component, and performing false color suppression processing and second noise reduction processing on the Cb component and the Cr component by using a memory allocated to the Cb component and the Cr component, where the Y component, the Cb component and the Cr component are variables of a YCbCr color space.
 2. The apparatus of claim 1, wherein the memory allocated to the Y component includes 2n (where n is a natural number) number of line memories, and the memory allocated to the Cb component and the Cr component includes 2n number of line memories.
 3. The apparatus of claim 1, wherein the Y component processing unit comprises: a first memory unit having memory allocated to the Y component, receiving the Y component, and generating Y matrix data; an edge region discrimination unit receiving the Y matrix data, detecting an edge, discriminating edge regions by using the detected edge, and outputting Y data of each region; and an edge enhancement and noise reduction unit receiving the Y data of each region, and generating edge-enhanced Y data and noise-reduced Y data.
 4. The apparatus of claim 3, wherein, when a size of an edge map of a corresponding pixel is smaller than a first edge value, the edge region discrimination unit outputs the Y matrix data corresponding to the pixel, as low edge Y data, when the size of the edge map of the corresponding pixel is greater than or equal to a second edge value that is greater than the first edge value, the edge region discrimination unit outputs the Y matrix data corresponding to the pixel, as high edge Y data, and when the size of the edge map of the corresponding pixel is greater than or equal to the first edge value and less than the second edge value, the edge region discrimination unit outputs the Y matrix data corresponding to the pixel, as middle edge Y data.
 5. The apparatus of claim 4, wherein the edge enhancement and noise reduction unit comprises: an edge enhancement unit receiving the high edge Y data and the middle edge Y data and generating the edge-enhanced Y data; and a Y noise reducer receiving the low edge Y data and generating the noise-reduced Y data.
 6. The apparatus of claim 1, wherein the CbCr processing unit comprises: a second memory unit having a memory allocated to the Cb component and the Cr component, receiving the Cb component and the Cr component, and generating Cb matrix data and Cr matrix data; a low pass filter low-pass-filtering the Cb matrix data and the Cr matrix data to generate filtered Cb data and filtered Cr data; and a false color suppression unit receiving the filtered Cb data and the filtered Cr data and generating false color-suppressed Cb data and false color-suppressed Cr data.
 7. A digital image processing method comprising: allocating memories to a Y component, a Cb component, and a Cr component; performing edge enhancement processing and first noise reduction processing on the Y component by using a memory allocated to the Y component; and performing false color suppression processing and second noise reduction processing on the Cb component and the Cr component by using a memory allocated to the Cb component and the Cr component.
 8. The method of claim 7, wherein the memory is a plurality of static random access memory (SRAM) type line memories, 2n (n is a natural number) number of memories are allocated to the Y component and 2n number of memories are allocated to the Cb component and the Cr component.
 9. The method of claim 8, further comprising: allocating n number of memories to the Cb component and allocating n number of memories to the Cr component.
 10. The method of claim 7, performing edge enhancement and first noise reduction processing, further comprises: calculating an edge map by using the Y component of a corresponding image, and determining an edge region to which a corresponding pixel belongs by using the edge map; setting a region gain of the corresponding pixel according to the edge region to which the corresponding pixel belongs; adjusting the region gain of the corresponding pixel according to illumination of the corresponding pixel to calculate an adjustment gain of the corresponding pixel; calculating a brightness difference of the corresponding pixel from the Y component of the image; and calculating an edge-enhanced Y component of the corresponding pixel by using the adjustment gain of the corresponding pixel and the brightness difference of the corresponding pixel.
 11. The method of claim 10, wherein, setting the region gain of the corresponding pixel further comprises: setting the region gain of the corresponding pixel to a low gain when the size of an edge map of a corresponding pixel is smaller than a first edge value; setting the region gain of the corresponding pixel to a high gain when the size of the edge map of the corresponding pixel is greater than or equal to a second edge value greater than the first edge value; and setting the region gain of the corresponding pixel to have a gain value determined in proportion to the size of the edge map of the corresponding pixel among gain values between the low gain and the high gain when the size of the edge map of the corresponding pixel is greater than or equal to the first edge value and smaller than the second edge value.
 12. The method of claim 11, wherein, calculating the adjustment gain of the corresponding pixel further comprises: setting the adjustment gain of the corresponding pixel to be equal to the region gain of the corresponding pixel when a size of the Y component of the corresponding pixel is greater than or equal to a first illumination value and smaller than a second illumination value; setting the adjustment gain of the corresponding pixel to have a gain value determined in proportion to a size of the Y component of the corresponding pixel among gain values between the low gain and the region gain of the corresponding pixel when the size of the Y component of the corresponding pixel is smaller than the first illumination value, the adjustment gain of the corresponding pixel is set to; and setting the adjustment gain of the corresponding pixel to a gain value determined to be inversely proportional to the size of the Y component of the corresponding pixel among gain values between the region gain of the corresponding pixel and the low gain when the size of the Y component of the corresponding pixel is greater than or equal to the second illumination value.
 13. The method of claim 10, where performing edge enhancement processing and first noise reduction processing further comprises performing noise reduction processing on the Y component of the image of a low edge region in which the size of the edge map is smaller than a first edge value to calculate a filtered Y component.
 14. The method of claim 13, wherein performing edge enhancement processing and first noise reduction processing further comprises generating an edge-enhanced Y component of a pixel, as a final Y component, when the size of the edge map of the pixel is greater than or equal to the first edge value, and generating the filtered Y component of the pixel, as a final Y component, when the size of the edge map is smaller than the first edge value.
 15. The method of claim 7, wherein performing false color suppression processing and second noise reduction processing further comprises: performing the second noise reduction processing on each of the Cb component of the image and the Cr component of the image to calculate a filtered Cb component and a filtered Cr component; and when false color suppression is enabled, performing false color suppression processing on the filtered Cb component and the filtered Cr component to generate a final Cb component and a final Cr component, and when the false color suppression is not enabled, generating the filtered Cb component and the filtered Cr component as the final Cb component and the final Cr component, respectively.
 16. The method of claim 15, wherein performing false color suppression processing and second noise reduction processing further comprises: performing the false color suppression processing on the corresponding pixel when the Y component of the corresponding pixel is smaller than a first illumination value or greater than or equal to a second illumination value that is greater than the first illumination value, when the corresponding pixel has a gray tone. 